الصفحة 1
الصفحة 1
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Information Processing in Medical Imaging ; 20th International Conference, IPMI 2007, Kerkrade, The Netherlands, July 2-6, 2007, Proceedings

The 20th International Conference on Information Processing in Medical Im- ing(IPMI)washeldduringJuly2–6,2007,atRolducAbbey,locatedinKerkrade in the south of the Netherlands. IPMI is one of the longest running conferences in medical imaging.

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Financial risk management with bayesian estimation of GARCH models : Theory and applications

This book presents methodologies for the Bayesian estimation of GARCH models and their application to financial risk management. The study of these models from a Bayesian viewpoint is relatively recent and can be considered very promising due to the advantages of the Bayesian approach, in particular the possibility of obtaining small-sample results and integrating these results in a formal decision model. The first two chapters introduce the work and give an overview of the Bayesian paradigm for inference. The next three chapters describe the estimation of the GARCH model with Normal innovations and the linear regression models with conditionally Normal and Student-t-GJR errors. The sixth chapter shows how agents facing different risk perspectives can select their optimal Value at Risk Bayesian point estimate and documents that the differences between individuals can be substantial in terms of regulatory capital.

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Applications of simulation methods in environmental and resource economics

Simulation methods are revolutionizing the practice of applied economic analysis. This volume collects eighteen chapters written by leading researchers from prestigious research institutions the world over. The common denominator of the papers is their relevance for applied research in environmental and resource economics. The topics range from discrete choice modeling with heterogeneity of preferences, to Bayesian estimation, to Monte Carlo experiments, to structural estimation of Kuhn-Tucker demand systems, to evaluation of simulation noise in maximum simulated likelihood estimates, to dynamic natural resource modeling. Empirical cases are used to show the practical use and the results brought forth by the different methods.

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